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There has been controversy regarding the air pollutants emitted from sources closely related to the activities of daily life in China, such as cooking, setting off fireworks, sacrificial incense and joss paper burning, and barbecue (which have been named the five missing sources – FMSs), and the extent to which they impact the outdoor air quality. To date, due to the lack of both an activity dataset and emission factors, there have been no estimations of the emission of air pollutants from FMSs. In this work, we have attempted to combine questionnaire data, various statistical data, and data on points of interest to obtain a relatively complete set of activity data. The emission factors (EFs) of carbonaceous aerosols were tested in our lab. Emission inventories of carbonaceous aerosols with a high spatial–temporal resolution for FMSs were then established, and the spatial variation trend and driving forces were discussed. From 2000 to 2018, organic carbon (OC) emissions were in the range of 4268–4919 t. OC emissions from FMSs were between 1.5 ‰ and 2.2 ‰ of the total emissions in China. Black carbon (BC), elemental carbon (EC), and brown carbon (BrC) absorption cross-section (ACS BrC) emissions from FMSs were in the ranges of 22.6–43.9 t, 213–324 t, and 14.7–35.6 Gm 2 , respectively. Their emissions tended to be concentrated in certain periods and areas. The OC emission intensities in central urban areas were 3.85–50.5 times those in rural areas (due to the high density of human activity), while the ACS BrC emissions in rural regions accounted for 63.0–79.5 % of the total emissions (resulting from uncontrolled fireworks). A mass of fireworks led to much higher ACS BrC and EC emissions on Chinese New Year's Eve, with respective values that were 1444 and 262 times their corresponding yearly averages. Significant (p<0.01) correlations between the population's income and pollutant emissions were also found: these correlations were positive (r=0.94) and negative (r=-0.94) for urban and rural regions, respectively, indicating the necessity to regulate residents' lifestyles and increase residents' income in respective urban and rural regions. This study provides firsthand data to identify emissions, variation trends, and impacting factors from the FMSs. This is helpful for modeling works on air quality, the climate effect, and human health risks during specific periods or in specific regions as well as for modifying emission control policies. The data compiled in this work can found at 10.6084/m9.figshare.19999991.v2 (Cheng et al., 2022). [ABSTRACT FROM AUTHOR]

The number of studies investigating the effects of ocean acidification on marine organisms and communities increases every year. Results are not easily comparable since the carbonate chemistry and ancillary data are not always reported in similar units and scales and are not calculated using similar sets of constants. To facilitate data comparison, a data compilation hosted by the PANGAEA Data Publisher was initiated in 2008 and is updated on a regular basis (10.1594/PANGAEA.962556; Ocean Acidification International Coordination Centre (OA-ICC), 2023). By November 2023, a total of 1501 datasets (over 25 million data points) from 1554 papers had been archived. To easily filter and access relevant biological response data from this compilation, a user-friendly portal (https://oa-icc.ipsl.fr , last access: 9 November 2023) was launched in 2018. Here, we present an update of this data compilation since its second description by Yang et al. (2016) and provide an overview of the OA-ICC portal for ocean acidification biological response data, launched in 2018. Most of the study sites from which data have been archived are in the North Atlantic Ocean, North Pacific Ocean, South Pacific Ocean, and Mediterranean Sea, while polar oceans are still relatively poorly represented. Mollusca and Cnidaria are still the best-represented taxonomic groups. The biological processes most reported in the datasets are growth and morphology. Other variables that can potentially be affected by ocean acidification and are often reported include calcification/dissolution, primary production/photosynthesis, and biomass/abundance. The majority of the compiled datasets have considered ocean acidification as a single stressor, but their relative contribution has decreased from 68 % before 2015 to 57 % today, showing a clear tendency towards more data archived from multifactorial studies. [ABSTRACT FROM AUTHOR]

There has been controversy about the air pollutants emitted from sources closely related to people's daily life (such as cooking, fireworks burning, sacrificial incenses and joss paper burning, and barbecue, named as five missing sources, FMS) impacting the outdoor air quality to what extent. Till now, there is no emission estimation of air pollutants from FMS, as the missing of both activity dataset and emission factors. We attempted to combine the questionnaire data, various statistical data, and data of points of interest to obtain a relatively complete set of activity data. The emission factors (EFs) of carbonaceous aerosols were tested in our lab. Then, the emission inventories of carbonaceous aerosol with the high spatial-temporal resolution for FMS were established firstly, and the spatial-variation trend and driving forces were discussed. From 2000 to 2018, organic carbon (OC) increased from 4268 t to 4919 t. The OC emission from FMS was 1.48-2.18 - of its total emission in China. The emissions of black carbon, element carbon (EC), and brown carbon absorption cross-section (ACSBrC) emissions from FMS were in the ranges of 22.6-43.9 t, 213-324 t, and 14.7-35.6 Gm2, respectively. Their emissions tended to concentrate in special periods and areas. The OC emission intensities in central urban areas were 3.85-50.5 times that of rural areas due to the high density of human activities. While the ACSBrC emissions in rural regions accounted for 63.0-79.5% of the total emission result from uncontrolled fireworks burning. A mass of fireworks burning led to extremely higher ACSBrC and EC emissions on Chinese New Year's eve, as 1444 and 262 times their corresponding yearly average values. Interestingly, significant (p<0.01) correlations between human incomes and pollutant emissions were found, but they were positive (r = 0.94) and negative (r = -0.94) for urban and rural regions, indicating the necessity of regulating human lifestyle and increasing income for urban and rural peoples, respectively. This study provided the first-hand data for identifying the emissions, variation trends and impacting factors of FMS, which is helpful for modeling works on air quality, climate effect, and human health risks at specific periods or regions and for modifying their emission control policies. The data in this work could be found at https://doi.org/10.6084/m9.figshare.19999991.v1 (Cheng et al., 2022). [ABSTRACT FROM AUTHOR]

In 3D building models, a large number of texture maps with different sizes increase the number of model data loading and drawing batches, which greatly reduces the drawing efficiency of the model. Therefore, this paper proposes a texture set mapping method based on vertex importance. Firstly, based on the 2D space boxing algorithm, the texture maps are merged and a series of Mipmap texture maps are generated, and then the vertex curvature, texture variability and location information of each vertex are calculated, normalized, and weighted to get the importance of each vertex, and then finally, different Mipmap-level textures are remapped according to the importance of the vertices. The experiment proves that the algorithm in this paper can reduce the amount of texture data on the one hand, and avoid the rendering pressure brought by the still large amount of data after merging on the other hand, so as to improve the rendering efficiency of the model. [ABSTRACT FROM AUTHOR]

The technological methods for digital documentation and the experimental best practice standards used to document and describe the many artistic objects determine the challenges and the numerous uses of today's cultural heritage.Because of this, it's crucial to preserve heritage by documenting it consciously and using conservation techniques that don't diminish or affect its worth. The study examines the issues we faced in disseminating all of the technical content we have, rather than focusing on the general importance of digital data for the technical staff. To share our heritage, we must make the digital legacy we have built over the last twenty years accessible. Starting from practical examples of dissemination projects in the context of conservation items, the analysis discusses an investigation into the findings and disciplinary culture that have resulted from research conducted by academics in the field of digital heritage on papers, conferences and EU projects produced and conducted between 2018 and 2022. The paper reviews the digital cultural heritage framework outlined by research up to this point.Our findings demonstrate that, despite the fact that the DCH area is constantly changing, we still primarily consider the technical side of digital without considering it as a genuine possibility for openness and sharing. [ABSTRACT FROM AUTHOR]

Humankind is known to be curious and inquisitive. Even if the code were lost, future individuals would be eager to find out what kind of message a printed paper offers. This was already the case when hieroglyphs were deciphered. Printed paper does not need additional equipment to be recognized as a data carrier. Therefore, paper as an analogue data store medium provides an interesting redundancy to deliver important information to future generations. The presentation deals with topics of age resistance of paper and inks as well as recommendations of how to empower printed or written paper to be a long-term data store. Different ageing conditions, different inks, different printing processes, and different fibre sources reveal the opportunities and threats. Data obtained during a 2-year-long project together with BASE (Bundesamt für die Sicherheit der nuklearen Entsorgung – Federal Authority for the Safety of Nuclear Waste Management) on the long-term stability of paper (Langzeitbeständigkeit von Papier – Labest Papier) emphasize the feasibility (Arbeitsstandberichte AP1–AP3 (literature, typical damage, recommendations), unpublished data). The ageing mechanisms of paper are known, as are countermeasures. This leads to standards and recommendations for the use of paper for documents. ISO 9706 (1994) is the main proponent of the direction that longevity can be ensured solely via the composition of the paper and the initial situation at the beginning of ageing. DIN 6738 (2007), on the other hand, takes as its basis the approach of assessing the physical ageing of the paper based on artificial ageing and the strength losses observed in the process. Other standards vary the approaches somewhat or mix them in part, for which the lecture presents a comparison table. The usability of a document depends on two essential factors. Firstly, the residual strength after an ageing process must be high enough for the document to be usable. Secondly, the information written on it must still be legible or at least recognizable (ISO 11798, 2023). However, although certain fibre resources that are recommended by different standards dealing with the long-term storage of documents as well as some fibre sources are denied, we must consider that all fibre sources undergo an ageing process. Different combinations of fibre and ink will lead to different results after natural or artificial ageing. This does not necessarily mean that only the best combination is able to fulfil the requirements related to transport information to an address in the far future. Albeit less strong or with higher optical changes, even by current standards, a rejected fibre source may nevertheless be able to keep the printed information over a long period of time. Paper has been a proven reliable information carrier for approx. 1000 years as the oldest known paper document archived in Palermo is from 1109 CE. It is reasonable to expect a reliability for many more years because the "Ebers" papyrus (worldwide longest, complete, and best-preserved papyrus scroll) stored at the University of Leipzig is already 3500 years old. Compared to modern information storage media such as digital media or microfilm, paper also has the advantage of a long migration time and that no reading or decoding device is necessary. Taking this into account, paper documents are predestined to play a major role in record, knowledge, and memory (RK&M) strategies, as described by Pescatore and Palm (2023). Finally, it remains to say that there can never be an intactness in the sense of being completely untouched. Paper, however, is a material consisting of natural polymers that prove their longevity in the world's oldest tree, a 9500-year-old spruce in Sweden. [ABSTRACT FROM AUTHOR]

This study aims on an exploration of recent applications of drones in the Malaysian context. More specifically, to investigate the drone's application status and application areas. To search the academic literature and identify the included documents, we have followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. We conducted an overview study of the total number of 54 documents (out of 202) published since 2018, which were extracted from the Scopus database. The results of the bibliometric analysis of the included documents showed that drones in Malaysia are applied in different disciplines, including agriculture, mapping, forestry, river monitoring, transportation, construction, coastal management, flood management, and other applications. Among these, agriculture and mapping are the main application areas. MDPI published the most journal articles, and IGRSM conferences published the highest number of conference papers. Furthermore, scholars from the Universiti Teknologi Malaysia have the highest contribution among others. [ABSTRACT FROM AUTHOR]

This paper explores digital education for pupils in a humanities teaching-learning lab. So far, digital humanities educational approaches have been primarily aimed at students. Teaching-learning labs, in which students design, implement and evaluate teaching offers for pupils, have so far almost exclusively existed in STEM subjects.Based on a classification in European frameworks and a literature analysis on teaching-learning labs of digital history education, the current state of the art on the topic is elucidated. Using concrete practical examples, the first results of involving students in digital history projects will be presented and suitable digital tools for teaching humanities content will be introduced. [ABSTRACT FROM AUTHOR]

Peatland restoration and rehabilitation action has become more widely acknowledged as a necessary response to mitigating climate change risks and improving global carbon storage. Peatland ecosystems require restoration time spans of the order of decades and, thus, cannot be dependent upon the shorter-term monitoring often carried out in research projects. Hydrological assessments using geospatial tools provide the basis for planning restoration works as well as analysing associated environmental influences. "Restoration" encompasses applications to pre-restoration and post-restoration scenarios for both bogs and fens, across a range of environmental impact fields. The aim of this scoping review is to identify, describe, and categorize current process-based modelling uses in peatlands in order to investigate the applicability and appropriateness of ecohydrological and/or hydrological models for northern peatland restoration. Two literature searches were conducted using the entire Web of Science database in September 2022 and August 2023. Of the final 211 papers included in the review, models and their applications were categorized according to this review's research interests in seven distinct categories aggregating the papers' research themes and model outputs. Restoration site context was added by identifying 229 unique study site locations from the full database, which were catalogued and analysed against raster data for the Köppen–Geiger climate classification scheme. A majority of northern peatland sites were in temperate oceanic zones or humid continental zones that experienced snow. Over one in five models from the full database of papers were unnamed and likely intended for single use. Key themes emerging from topics covered by papers in the database included the following: modelling restoration development from a bog growth perspective, the prioritization of modelling greenhouse gas (GHG) emissions dynamics as a part of policymaking, the importance of spatial connectivity within or alongside process-based models to represent heterogeneous systems, and the increased prevalence of remote sensing and machine learning techniques to predict restoration progress with little physical site intervention. Models are presented according to their application to peatlands or broader ecosystem and organized from most to least complex. This review provides valuable context for the application of ecohydrological models in determining strategies for peatland restoration and evaluating post-intervention development over time. [ABSTRACT FROM AUTHOR]

The world is experiencing an unprecedented rate of urbanisation, with 70% of its population expected to live in urban cities by 2050 (United Nations, 2018). This is driving demand for smart city development projects, that address city related issues such as traffic congestion, inadequate housing, excessive crime rates, strains on utilities like energy and water, amongst others. The volume and analysis of data associated with these activities, call for a mechanism for managing data in smart cities.This paper is aimed at developing a data governance framework for managing data generated by smart cities, and improving the way they operate as well as the quality of life of their citizens. The paper will highlight the characteristics of smart cities, the importance for cities to become smart, how the smartness of cities can be measured, and which cities around the world are considered smart. It will also discuss why data is important for the success of smart cities, the types and sources of data typically present in smart city settings and the data management challenges that plague smart cities globally.A sequential mixed methods research approach incorporating qualitative and quantitative data collection and analysis methods was employed, following a multi-step approach starting with analysis of existing frameworks and interviews with subject matter experts. This was followed by a survey of industry professionals, for insights on key framework components, and the use of case studies and questionnaires for framework evaluation.Throughout the research process, the focus of smart cities on people rather than technology was prominent. As such, the most important theme of the framework was identified as "People", particularly in their roles as data stewards and data owners. The remaining five themes of the recommended data governance framework are, Process, Technology, Data, Protection and Valuable Insights. [ABSTRACT FROM AUTHOR]

Understanding carbon sources and sinks across the Earth's surface is fundamental in climate science and policy; thus, these topics have been extensively studied but have yet to be fully resolved and are associated with massive debate regarding the sign and magnitude of the carbon budget from global to regional scales. Developing new models and estimates based on state-of-the-art algorithms and data constraints can provide valuable knowledge and contribute to a final ensemble model in which various optimal carbon budget estimates are integrated, such as the annual global carbon budget paper. Here, we develop a new atmospheric inversion system based on the 4D local ensemble transform Kalman filter (4D-LETKF) coupled with the GEOS-Chem global transport model to infer surface-to-atmosphere net carbon fluxes from Orbiting Carbon Observatory-2 (OCO-2) V10r XCO 2 retrievals. The 4D-LETKF algorithm is adapted to an OCO-2-based global carbon inversion system for the first time in this work. On average, the mean annual terrestrial and oceanic fluxes between 2015 and 2020 are estimated as - 2.02 and - 2.34 GtC yr -1 , respectively, compensating for 21 % and 24 %, respectively, of global fossil carbon dioxide (CO 2) emissions (9.80 GtC yr -1). Our inversion results agree with the CO 2 atmospheric growth rates reported by the National Oceanic and Atmospheric Administration (NOAA) and reduce the modeled CO 2 concentration biases relative to the prior fluxes against surface and aircraft measurements. Our inversion-based carbon fluxes are broadly consistent with those provided by other global atmospheric inversion models, although discrepancies still occur in the land–ocean flux partitioning schemes and seasonal flux amplitudes over boreal and tropical regions, possibly due to the sparse observational constraints of the OCO-2 satellite and the divergent prior fluxes used in different inversion models. Four sensitivity experiments are performed herein to vary the prior fluxes and uncertainties in our inversion system, suggesting that regions that lack OCO-2 coverage are sensitive to the priors, especially over the tropics and high latitudes. In the further development of our inversion system, we will optimize the data-assimilation configuration to fully utilize current observations and increase the spatial and seasonal representativeness of the prior fluxes over regions that lack observations. [ABSTRACT FROM AUTHOR]

Floods kill numerous people every year in both developed and developing countries. The transfer of research findings from the academic community to practitioners, policy-makers and citizens may reduce the impact of floods on mortality. This systematic review analyzes 44 scientific articles extracted from WOS and SCOPUS databases written in English, published between 2010 and 2020, and focuses on flood fatalities. The first main finding of this review is the classification of drivers of flood mortality into two groups: the first group relates to the environment, and the second group relates to the fatalities. The second main finding is the identification of strategies to practically cope with the identified drivers of flood fatalities. The main shortcomings of the review concern (a) the unavailability of papers based on flood fatality occurrence in developing countries and (b) the absence of data focusing on people who have survived floods. This review amplifies useful findings, best practices and lessons learned that can be useful for administrators, risk managers, and teachers of primary and secondary schools to mitigate the impact of future floods on human life. [ABSTRACT FROM AUTHOR]

Which published papers have transformed our understanding of the chemical processes in the troposphere and shaped the field of atmospheric chemistry? By way of expert solicitation and interactive peer review, this paper explores the influence of the ideas in peer-reviewed articles based on input from our community of atmospheric scientists. We explore how these papers have shaped the development of the field of atmospheric chemistry and identify the major landmarks in the field of atmospheric chemistry through the lens of those papers' impact on science, legislation and environmental events. We also explore the ways in which one can identify the papers that have most impacted the field and discuss the advantages and disadvantages of the various approaches. Our work highlights the difficulty of creating a simple list, and we explore the reasons for this difficulty. The paper also provides a history of the development of our understanding of tropospheric chemistry and points some ways for the future. [ABSTRACT FROM AUTHOR]

In December 2020 the ICA joined the Open Geospatial Consortium (OGC) as an associate member. As a community composed of businesses, government agencies, universities, and research organizations that work with geospatial data, the OCG is a resource to which software developers who work with geospatial data turn for guidance and advice. As such, it provides the ICA with an opportunity to reach a group of people who might not have had prior experience or background in cartography. [ABSTRACT FROM AUTHOR]

To mark the 20th anniversary of Natural Hazards and Earth System Sciences (NHESS), an interdisciplinary and international journal dedicated to the public discussion and open-access publication of high-quality studies and original research on natural hazards and their consequences, we highlight 11 key publications covering major subject areas of NHESS that stood out within the past 20 years. The papers cover all the topics contemplated in the European Geosciences Union (EGU) Division on Natural Hazards including dissemination, education, outreach and teaching. The selected articles thus represent excellent scientific contributions in the major areas of natural hazards and risks and helped NHESS to become an exceptionally strong journal representing interdisciplinary areas of natural hazards and risks. At its 20th anniversary, we are proud that NHESS is not only used by scientists to disseminate research results and novel ideas but also by practitioners and decision-makers to present effective solutions and strategies for sustainable disaster risk reduction. [ABSTRACT FROM AUTHOR]

In recent years, deep convolutional neural networks (CNNs) algorithms have demonstrated outstanding performance in a wide range of remote sensing applications, including image classification, image detection, and image segmentation. Urban development, as defined by urban expansion, mapping impervious surfaces, and built-up areas, is one of these fascinating issues. The goal of this research is to explore at and summarize the deep learning approaches used in urbanization. In addition, several of these methods are highlighted in order to provide a comprehensive overview and comprehension of them, as well as their pros and downsides. [ABSTRACT FROM AUTHOR]

Rainbow colour maps are known to be problematic yet remain widely used in scientific communication. This study extends work by Stoelzle and Stein (2021) to investigate the extent of their use in geoscience publications. It is found that over half (55 %) of all papers surveyed from six geoscience journals from the years 2005, 2010, 2015 and 2020 (n=2638) contained at least one visualisation that uses rainbow or red–green colour schemes and are therefore potentially misleading and colour-inaccessible. Recent changes to the submission guidelines for all European Geosciences Union (EGU) journals would seem to place greater responsibility in the future with editors and reviewers to identify and correct colour issues as part of the review process. [ABSTRACT FROM AUTHOR]

Structural connectivity is an important factor in preserving coral diversity. It maintains the stability and adaptability of coral reef ecosystems by facilitating ecological flow, species migration, and gene exchange between coral communities. However, there has always been a lack of consistent solutions for accurate structural connectivity describing and quantifying, which has hindered the understanding of the complex ecological processes in coral reefs. Based on this, this paper proposes a framework that uses advanced remote sensing and deep learning technologies to assess coral structural connectivity. Specifically, accurate coral patches are firstly identified through image segmentation techniques. And the structural connectivity is quantified by assessing the connectivity patterns between and within these coral patches. Furthermore, Tetiaroa Island in the South Pacific is used as a case study to validate the effectiveness and accuracy of the framework in assessing coral structural connectivity. The experimental results demonstrate that the framework proposed in this paper provides a powerful tool for understanding the internal ecological processes and external spatial patterns of coral reef ecosystems, thereby promoting scientific understanding and effective management of coral reef conservation. [ABSTRACT FROM AUTHOR]

The preface to the Proceedings of the 8th Smart Data Smart Cities (SDSC) conference provides an overview of the concept of a Smart City, which involves the use of digital layers for city governance, citizen services, and sustainable development. Smart Cities utilize intelligent technology to enhance urban life by integrating data from various sources such as sensors, demographics, mapping, and building information models. The conference focuses on the use of spatial information and communication technologies in Smart Cities, covering topics such as 3D modeling, citizen engagement, transportation, urban decision-making, and smart urban mobility. The volume consists of 31 research papers selected through blind review, addressing different aspects of Smart Cities. [Extracted from the article]

Decades of decline, disinvestment, and racism have left Detroit with an abundance of abandoned buildings, ruins, vacant lots, and illicit trash dumps. Though these structures and materials might have forfeited their previous purposes, they can act as catalysts, substances, and co-creators of artworks. The paper is thus interested in examining the intricate interplay between art, space, and materiality in Detroit further. Drawing from the practices of local artists Olayami Dabls and Scott Hocking, the paper adopts a new materialist framework to investigate the dynamic agency of matter in the artistic process. By considering materials as active participants in the production of art and space, the paper seeks to add to the emerging interest in the emancipation and meaning making of material in art as well as cultural geography's engagements with new materialism. [ABSTRACT FROM AUTHOR]

With the wide use of UAVs in urban scenes making image acquisition easier, processing large-scale 3D reconstruction problems have become a basic need of the Structure from Motion (SfM) community. Because of high memory consumption and computation complexity, bundle adjustment (BA) is a significant bottleneck in large-scale 3D reconstruction problems. Distributed strategy is a current research direction. Recent research cut the view graph to optimize sub-scenes in small size and average common cameras and/or 3D points to align them into one in the end. Yet, those methods tried to simply average cameras and/or 3D points, which lack mathematical rigor and tend to get a sub-optimal result. This paper first cuts the view graph and expands it. Then we use the strategy of motion averaging instead of simply averaging points to obtain a robust result. Finally, refined results are achieved by optimizing reprojection errors in the overlapping area. We conduct experiments on UAV data, check the validity of graph cut and expansion, and analyze whether graph size influences the precision computation time. Visualization results show that our method preserves scenes well; precision and visualization of un-expanded scenes prove the necessity of graph expansion; statistical results also indicate the negative infect of large sub-scene size. [ABSTRACT FROM AUTHOR]

Keyframes extraction is required and effective for the 3D reconstruction of objects from a thermal video sequence to increase geometric accuracy, reduce the volume of aerial triangulation calculations, and generate the dense point cloud. The primary goal and focus of this paper are to assess the effect of keyframes extraction from the thermal infrared video sequence on the geometric accuracy of the dense point cloud generated. The method of keyframes extraction of thermal infrared video presented in this paper consists of three basic steps. (A) The ability to identify and remove blur frames from non-blur frames in a sequence of recorded frames. (B) The ability to apply the standard baseline condition between sequence frames to establish the overlap condition and prevent the creation of degeneracy conditions. (C) Evaluating degeneracy conditions and keyframes extraction using Geometric Robust Information Criteria (GRIC). The performance evaluation criteria for keyframes extraction in the generation of the thermal infrared dense point cloud in this paper are to assess the increase in density of the generated three-dimensional point cloud and reduce reprojection error. Based on the results and assessments presented in this paper, using keyframes increases the density of the thermal infrared dense point cloud by about 0.03% to 0.10% of points per square meter. It reduces the reprojection error by about 0.005% of pixels (2 times). [ABSTRACT FROM AUTHOR]

Machine learning (ML) has played an increasing role in the hydrological sciences. In particular, Long Short-Term Memory (LSTM) networks are popular for rainfall–runoff modeling. A large majority of studies that use this type of model do not follow best practices, and there is one mistake in particular that is common: training deep learning models on small, homogeneous data sets, typically data from only a single hydrological basin. In this position paper, we show that LSTM rainfall–runoff models are best when trained with data from a large number of basins. [ABSTRACT FROM AUTHOR]

Floods kill several people every year in both developed and developing countries. The transfer of research findings from the academic community to practitioners, policy-makers and citizens may reduce the impact of floods on mortality. This systematic review analyzes 44 scientific articles extracted from WOS and SCOPUS databases written in English, published between 2010 and 2020, and focuses on flood fatalities. The first main finding of this review is the classification of drivers of flood mortality into two groups: the first group relates to the environment and the second group relates to the victims. The second main finding is the identification of strategies to practically cope with the identified drivers of flood fatalities. The main lacks of the review concern: a) the unavailability of papers based on flood fatality occurrence in developing countries and b) the absence of data focusing on people who have survived floods. This review amplifies useful findings, best practices, and lessons learned that can be useful for administrators, risk managers, and teachers of primary and secondary schools to mitigate the impact of future floods on human life. [ABSTRACT FROM AUTHOR]

Over the last decades, the concept of map visual complexity has been extensively investigated in cartographic research. Existing approaches provide specific measures and metrics which can be utilized towards the objective examination of map effectiveness, e.g. Monmonier (1974), MacEachrean (1982), Fairbairn (2006), and Rautenbach et al. (2015). Moreover, recent studies analyze behavioral data, e.g. Cybulski (2020), Tzelepis et al. (2020), using cartographic products distributed in the internet (Schnur et al., 2018). However, map visual complexity could be affected by several factors. Among them, map scale seems to play a significant role, since it is connected to the accuracy and the level of information delivered by a cartographic product (Dumont et al., 2020). In this work, the concept of map visual complexity is connected to visual heterogeneity. A new method for quantifying visual heterogeneity of paper maps is proposed. The method is based on diffuse reflectance spectroscopy and on a random segmentation and sampling in maps with different scale levels. It is shown that by using certain segmentation size, an indicator based on Shannon entropy of the samples can be efficient in characterizing the visual heterogeneity and the scale of the maps. A low-cost optical spectrometer is utilized in order to record the spectra of 40 random segments of the maps. Reflectance spectroscopy aims at measuring the relative level of reflected light as it is compared with a reference (white surface) to record a percentage value at each wavelength and for each segment of the map. A bifurcated optical fiber has been used to deliver the reference light to the map surface (Halogen light source), while the reflected light is guided to the spectrometer (Figure 1). Segment size is defined by moving the fiber closer to the map surface and it is expected to significantly affect the estimation of the indicator. In the present experiments, the distance of the fiber from the map surface is such so that the diameter of the randomly selected segments is approximately 3 mm. The spectrometer spectral resolution is approximately 1.5 nm and, consequently, more than 240 spectral channels are recorded for each sample, since only the visible region of the spectrum is required (380 nm - 750 nm). The proposed heterogeneity indicator is the Shannon entropy, as is calculated by the probabilities to record similar reflection spectral values (relative reflected light) in the space defined by the 40 samples of each map. Since the spectral values are continuous variables, they have to be properly quantized (discretization process), before the probabilities and the entropy are calculated. In addition, Principal Component Analysis (PCA) can be also utilized in order to reduce the spectral data dimensions (channels) and to enable faster calculations. As a means to evaluate the proposed indicator, 60 different paper maps are used. Maps' production is based on the use of the standard layer of OpenStreetMap (OSM) as it is provided by the Web Map Service (WMS) of terrestris GmbH & Co. KG. OSM cartographic backgrounds are utilized in this work because they present adequately high information (content) density and diversity across different scale -- or zoom -- levels compared to other online map services, e.g. Google Maps, Here WeGo, etc. (Skopeliti and Stamou, 2019). More specifically, for the needs of this research study, twenty regions in Greece and three different map scale levels (1:k, 1:4k, & 1:40k) are examined. The produced maps are printed using the same paper quality. Box plots are applied to show the indicator with respect to the scale. It is shown that the scale of the map strongly affects the information content and the visual heterogeneity of the map. [ABSTRACT FROM AUTHOR]

In the Swiss National Forest Inventory (NFI), information about the current condition and the changes of the Swiss forest is regularly collected (Brändli et al. (2020)). Data collection consists of on-the-ground surveys, remote-sensing analyses and an interview survey with the district foresters. The interview survey takes place every nine years and includes an update of the current situation of the forest road network, consisting of roads that can be used for wood extraction and transport. Information on the location of roads and their characteristics, such as the suitability for different vehicle classes, is important to assess the accessibility of the forest and to estimate costs for wood harvesting and transport. In all forest road surveys conducted up to now the forest road network was updated by drawing lines and writing predefined codes on paper maps by hand. In the third and fourth survey, information on road properties was later combined with existing digital road geometries, producing a spatial digital road dataset which could be analysed in a GIS (Fraefel and Fischer (2019)). However, the process to transfer the mapped properties from the paper maps to the digital road geometries (scanning, georeferencing, attribute entry) was very time-consuming. In addition, the growing number of road properties in the survey made it difficult to clearly display all the existing information on a fixed-scale paper map. For the current (fifth) NFI forest road survey, we have therefore developed a procedure that allows the interviewer to collect information about road network changes directly in a GIS, together with the forester, at the forester's office. This requires a user interface that plays together with a touch interface to make data entry similar to pen-and-paper mapping, easy to use even for non-GIS-specialists. At the same time, the system should be sufficiently mobile to be transported by car and offer a large screen for the clear representation of the previously collected information and easy map navigation within the survey area. Various tests and comparisons included different ways of manipulating existing features and drawing new ones; different touch interfaces; the display of information in the map; and the set-up of the user interface with, for example, custom buttons. The resulting tool has a number of benefits, compared to a survey on paper maps: no scanning and georeferencing is required (cost reduction); faster attribute assignment (from digital lines to existing road geometries); value domains and consistency constraints for data entry; the possibility to alert the interviewer to specific locations by turning layers on and off; and faster data availability through online transmission, if required. A drawback of the method is the need for additional hardware (screens and pen tablets) and some training with regard to the hardware and GIS software. [ABSTRACT FROM AUTHOR]

Due to the increase in the frequency and intensity of natural disasters such as heavy rainfall events, the evaluation of the vulnerability of the built environment is becoming increasingly important. Evaluation techniques for each separate building often require detailed geometric models of the supporting structures and time-consuming simulations. One possibility to overcome this problem is to categorize the buildings in a first step and use representative building models for each category. This paper presents a semi-automated approach for categorizing buildings and creating parametric models for the respective building categories. Using these models, the buildings of a category can be collectively examined for their vulnerability to various impacts. First, this paper introduces open geodata that can be used for this process. For the categorization of the buildings, the collected data is further processed to extract additional information such as building age classes or floor plan geometries of the buildings. This results in a data set, with the help of which the buildings can be categorized. However, information about the load-bearing structure is often missing in the different data sources. By including information on typical construction methods that are associated with the previously determined characteristics (age, floor plan geometry, usage), representative models can be created for individual building categories. In this study, the approach was tested in a selected reference area in Berlin. The results indicate that the presented approach is a promising first step towards deriving geometrical models from open geodata that can be used to evaluate the vulnerability of buildings. [ABSTRACT FROM AUTHOR]

The technology for 3D reconstruction of tree models based on point clouds has been extensively researched, necessitating effective datasets for the study of branch and leaf separation, skeleton point extraction, and tree parameter extraction methods. However, existing datasets for 3D tree models face several challenges, including insufficient data volume for deep learning network training, low accuracy of model ground truth impeding effective method precision evaluation, and a lack of dataset richness to satisfy the needs of multi-type method assessments. In response to these challenges, This paper introduces, for the first time, a fully automated method for generating structured three-dimensional synthetic tree models, and constructs a large-scale 3D synthetic tree dataset enriched with comprehensive structural information. This method facilitates automated computation across several processes, including the mass generation of simulated trees, separation of branches and leaves, noise generation, extraction of skeleton points, and volume calculation. To validate the usability of this dataset across various applications, this paper employs state-of-the-art (SoTA) algorithms to verify the accuracy of methods in 3D tree model reconstruction and carbon stock calculation, thereby thoroughly demonstrating the dataset's effectiveness. [ABSTRACT FROM AUTHOR]

The preparation of laser scanning missions is important for efficiency and data quality. Furthermore, it is a prerequisite for automated data acquisition, which has numerous applications in the built environment, including autonomous inspections and monitoring of construction progress and quality criteria. The scene and potential scanning locations can be discretized to facilitate the analysis of visibility and quality aspects. The remaining mathematical problem to generate an economic scan strategy is the Viewpoint Planning Problem (VPP), which asks for a minimum number of scanning locations within the given scene to cover the scene under pre-defined requirements. Solutions for this problem are most commonly found using heuristics. While these efficient methods scale well, they cannot generally return globally optimal solutions. This paper investigates the VPP based on a problem description that considers quality-constrained visibility in 3D scenes and suitable overlaps between individual viewpoints for targetless registration of acquired point clouds. The methodology includes the introduction of a preprocessing method designed to simplify the input data without losing information about the problem. The paper details various solution methods for the VPP, encompassing conventional heuristics and a mixed-integer linear programming formulation, which is solved using Benders decomposition. Experiments are carried out on two case study datasets, varying in specifications and sizes, to evaluate these methods. The results show the actual quality of the obtained solutions and their deviation from optimality (in terms of the estimated optimality gap) for instances where exact solutions can not be achieved. [ABSTRACT FROM AUTHOR]

This paper discusses the representation of the scale dimension using tGAP/SSC-DHE, emphasizing its role in creating vario-scale representations. It outlines the process of integrating the scale dimension as the third dimension in a 2D map before transitioning to 3D or 4D maps. DHE is introduced as an effective data structure for this approach, maintaining crucial connections across different levels of detail and offering enhanced topology. Its strength lies in the ability to modify specific parts of the model while retaining a clear structure, thanks to well-defined operators such as Euler operators. This method provides a versatile framework for representing complex spatial data, allowing for detailed analysis while preserving overall coherence and it updates the shape and structure of the model at the same time through local modifications. Through practical implementation, it demonstrates the potential for improved visualization and understanding of multi-dimensional spatial relationships. Also, the DHE data structure supports slicing by either a horizontal plane to produce a map at a specific scale (depending on the height of the horizontal plane) and tilted planes to produce perspective views with mixed scales. [ABSTRACT FROM AUTHOR]

The potential of Building Information Models (BIM) to establish rights and responsibilities for multi-level building complexes in cadastral registrations has been explored in many previous researches. However, the implementation of BIM-based cadastral registrations in practice remains limited due to the complex interplay between technical potentials and legal implications as well as uncertainty about the additional complexity of a BIM model and the extra work that will be required to generate the BIM Legal model. In collaboration with Netherlands Kadaster, we have investigated the data requirements for a BIM Legal model that will support the 3D cadastral registration of apartment complexes and that aligns with BIM creation processes in practice. The BIM Legal model aims to visualise the spatial aspects of apartment complexes and to align the cadastral registration to the 3D data that is generated in the design and construction phase of new buildings. The BIM Legal file will be submitted when an apartment complex is being registered and is based on IFC, the open standard established by BuildingSMART International and used in the BIM domain. To make the implementation of BIM Legal feasible legally, technically, and economically, we apply a 3-phase approach. This paper presents the BIM Legal model as defined in Phase 1, which enables to generate a BIM Legal model compliant with current legislation frameworks with no/minimal manual interaction from BIM models as commonly generated in design processes. The paper describes the 3-phase approach, the context of Phase 1, the data requirement analyses, the defined BIM Legal data model, as well the questions that emerged during the specification process that need to be answered to further improve the implementation of Phase 1 and to further develop BIM Legal for Phases 2 and 3. [ABSTRACT FROM AUTHOR]

With the increase of remote sensing image acquisition methods and the number of remote sensing image data, the traditional manual annotation and recognition methods can no longer meet the needs of the present production life. This study explores the use of deep learning techniques to improve the efficiency and accuracy of target detection in remote sensing satellite images, especially for small targets. Traditional target detection methods often face challenges in recognition accuracy and processing speed due to the specificity and complexity of satellite images, such as large size, variable lighting conditions and complex background. Therefore, this paper adopts the YOLOv5 model and introduces the CBAM (Convolutional Block Attention Module) attention mechanism, which significantly improves the detection of small and dense targets. Experimental validation, using the improved YOLOv5 model on the VisDrone2021 dataset, demonstrates that the model improves the mean average percision (mAP) by 1.9% while maintaining realtime performance. This paper provides new ideas for remote sensing image processing, especially for applications in the fields of urban planning and automatic driving, etc. Despite the progress made in this study, the detection of small targets in remote sensing images, the limited classification accuracy and the detection of dynamic targets still need further research. [ABSTRACT FROM AUTHOR]

As urbanization accelerates, traffic congestion and frequent accidents have become prominent issues, prompting the development of intelligent transportation systems. This paper focuses on the research of vehicle and pedestrian detection algorithms to improve detection accuracy in complex traffic environments. Considering the limitations of traditional object detection algorithms in complex situations, this study adopts the deep learning-based YOLOv8 algorithm and introduces the Coordinate Attention (CA) module to enhance the model's feature extraction and localization capabilities. Experimental results show that the improved YOLOv8 network achieves a 1.1% increase in detection accuracy while maintaining its original speed. Furthermore, this paper constructs a vehicle and pedestrian dataset suitable for Chinese traffic scenes, providing an effective solution for autonomous driving assistance systems. Overall, this study holds significant reference value for vehicle and pedestrian detection in the field of intelligent transportation. [ABSTRACT FROM AUTHOR]

This paper investigates the challenges of implementing the CityGML standard within database environments for managing urban digital twins (UDT), with a particular focus on addressing big geodata issues. CityGML stands as a critical standard for representing and exchanging 3D urban models and thematic data, essential for effective urban planning and infrastructure management. However, integrating CityGML into databases poses challenges due to the dual requirements of geospatial and semi-structured data. While the former imposes a certain rigor in its formalism, the second benefits from more flexibility. Through a comprehensive review and benchmarking of existing database implementations, including both new distributions and those often use, 3DCityDB, CJDB, Measur3D, and Cerbere, this paper proposes a novel approach towards a multi-database CityGML environment tailored to the specific needs of UDT. The proposed solution leverages the strengths of both relational and NoSQL databases, offering a flexible and scalable architecture while ensuring data consistency, geospatial capabilities and compliance with the CityGML schema. The research hypothesis suggests integrating Cerbere, a middleware for CityGML schema compliance and transaction validation, with 3DCityDB and Measur3D (MongoDB). This approach aims to demonstrate the feasibility of managing advanced 3D data operations based on the CityGML model (3DCityDB) and scalability for big data like IoT (Measur3D) within a multi-database environment. The paper contributes to the advancement of UDT by providing a comprehensive solution for managing diverse data types, facilitating more effective urban planning, infrastructure management, and sustainable development initiatives in the context of smart cities. [ABSTRACT FROM AUTHOR]

To mark the twentieth anniversary of Natural Hazards and Earth System Sciences (NHESS), an interdisciplinary and international journal dedicated to the public discussion and open-access publication of high-quality studies and original research on natural hazards and their consequences, we highlight eleven key publications covering major subject areas of NHESS that stood out within the past 20 years. The selected articles represent excellent scientific contributions in the major areas of natural hazards and risks and helped NHESS to become an exceptionally strong journal representing interdisciplinary areas of natural hazards and risks. At its 20th anniversary, we are proud that NHESS is not only used by scientists to disseminate research results and innovative novel ideas but also by practitioners and decision-makers to present effective solutions and strategies for sustainable disaster risk reduction. [ABSTRACT FROM AUTHOR]

Harvesting usable and meaningful disaster-related, spatio-temporal data at a highly granular level poses major challenges in its cleaning and aggregation. This paper presents a strategy related to those challenges with respect to individual behavior near COVID-19 laden healthcare facilities. This is done to enable the visualizing of egress behavior data as interactive, three-dimensional (3D) scenes to investigate human behavior patterns regarding touch-based, disease transmission. Therefore, the aim is to demonstrate how this concept of 3D epidemiology may provide new mechanisms to understand the relative risk and exposure prevalence for data analysis. This paper demonstrates 3D enablement of disaster-related field data through use of first-hand observations of 1,936 individuals egressing New York City healthcare facilities during the onset of COVID-19 in the Spring of 2020. The observations capture egress behavior in terms of where people go (e.g. coffee shop, Subway) and how they physically interact with the surroundings (i.e. what they touch and how long they remain). This paper introduces a mechanism for automated extraction and 3D visualization of such data in Potree, an open-source Web Graphics Library (WebGL) point cloud viewer. Distinctive vertex shaders are used to distinguish specific destination selection and behavioral patterns (e.g. personal protective equipment usage). Two-dimensional heatmaps are paired with 3D scenes to demonstrate the potential of using 3D visualization of spatio-temporal patterns for visualizing disease transmission potential. [ABSTRACT FROM AUTHOR]

The paper deals with the wind speed of strong and extreme wind events in Poland and their descriptions of their effects. Two recent estimation developed by the Institute of Meteorology and Water Management in Warsaw [4] and by Lorenc [3] are presented. Their strong and weak points are briefly described. The 37 annual maximum gusts of wind speeds measured at all meteorological stations between 1971 and 2007 are analysed with extremal probability paper. Based on the measured and estimated wind speeds (taken from existing literature), the authors suggest new estimations for strong and extreme wind that may occur in Poland. In the near future, Poland is going to construct some important structures, such as a central air terminal and some nuclear power plants, so knowledge about strong and extreme winds in our country is very important for engineers who will design these types of structures. In this case, the information given in Section 6 of the ISO 1382 standard for identifying hazards, estimating, evaluating, and treating risk may be applied. [ABSTRACT FROM AUTHOR]

Long-term experimental stratospheric NO 2 and NO partial columns measured by means of solar Fourier-transform infrared (FTIR) spectrometry at Zugspitze (47.42° N, 10.98° E; 2964 m a.s.l.), Germany, were used to create a set of experiment-based monthly scaling factors (SF exp). The underlying data set is published in a companion paper (Nürnberg et al., 2024) and comprises over 25 years of measurements depicting the daytime variability of stratospheric NO 2 and NO partial columns with respect to local solar time (LST). In accordance with simulation-based scaling factors recently published by Strode et al. (2022), we created SF exp normalized to SZA =72° for NO 2 and NO for every month of the year as a function of solar zenith angle (SZA). Apart from a boundary value problem at minimum SZA values originating from averaging over different times of the month, the obtained scaling factors SF exp (NO 2) and SF exp (NO) as a function of SZA represent the daytime behavior already shown in model simulations and experiments in the literature very well. This shows a well-pronounced increase in the NO 2 and NO stratospheric partial column with the time of the day and a flattening of this increase after noon. In addition to the discussion of SF exp , we validate the simulation-based scaling factors SF sim (NO 2) (Strode et al., 2022) and present simulation-based scaling factors for NO SF sim (NO). The simulation-based scaling factors show excellent agreement with the experiment-based ones; i.e., for NO 2 and NO the mean value of the modulus between the experiment and simulation over all SZAs and months is only 0.02 %. We show that recently used model simulations can describe the real behavior of nitrogen oxide (NO x) variability in the stratosphere very well. Furthermore, we conclude that ground-based FTIR measurements can be used for validation of the output of photochemistry models and for creating experiment-based data sets describing the daytime stratospheric NO x variability as a function of SZA. This is a contribution to improved satellite validation and a better understanding of stratospheric photochemistry. [ABSTRACT FROM AUTHOR]

ATLID (ATmospheric LIDar) is the lidar flown on the multi-instrument Earth Cloud Aerosol and Radiation Explorer (EarthCARE). EarthCARE is a joint ESA–JAXA mission that was launched in May 2024. ATLID is a three-channel, linearly polarized, high-spectral-resolution lidar (HSRL) system operating at 355 nm. Cloud and aerosol optical properties are key EarthCARE products. This paper provides an overview of the ATLID Level 2a (L2a; i.e., single instrument) retrieval algorithms being developed and implemented in order to derive cloud and aerosol optical properties. The L2a lidar algorithms that retrieve the aerosol and cloud optical property profiles and classify the detected targets are grouped together in the so-called A-PRO (ATLID-profile) processor. The A-PRO processor produces the ATLID L2a aerosol product (A-AER); the extinction, backscatter, and depolarization product (A-EBD); the ATLID L2a target classification product (A-TC); and the ATLID L2a ice microphysical estimation product (A-ICE). This paper provides an overview of the processor and its component algorithms. [ABSTRACT FROM AUTHOR]

In this paper, we describe a method for retrieving the surface emissivity of specular surfaces across the wavenumber range of 400–1600 cm -1 using novel radiance measurements of the Far-INfrarEd Spectrometer for Surface Emissivity (FINESSE) instrument. FINESSE is described in detail in Part 1 of this paper. We apply the method to two sets of measurements of distilled water. The first set of emissivity retrievals is of distilled water heated above ambient temperature to enhance the signal-to-noise ratio. The second set of emissivity retrievals is of ambient temperate water at a range of viewing angles. In both cases, the observations agree well with calculations based on compiled refractive indices across the mid- and far-infrared. It is found that the reduced contrast between the up- and downwelling radiation in the ambient temperature case degrades the performance of the retrieval. Therefore, a filter is developed to target regions of high contrast, which improves the agreement between the ambient temperature emissivity retrieval and the predicted emissivity. These retrievals are, to the best of our knowledge, the first published simultaneous retrievals of the surface temperature and emissivity of water that extend into the far-infrared and demonstrate a method that can be used and further developed for the in situ retrieval of the emissivity of other surfaces in the field. [ABSTRACT FROM AUTHOR]

Lightning protection is important for weather radars to prevent critical damage or outages, but this can have negative effects on data quality. The existing lightning protection of the German Meteorological Service (Deutscher Wetterdienst, DWD) polarimetric C-band weather radar network consists of four vertical poles with a maximum diameter of 10 cm. During radar operation, these rods cause local scattering in the near field of the antenna, resulting in negative impacts on radar products. One effect is the removal of significant transmission power from the main beam axis and its addition to other areas or the side lobes. This results in wrongly localised precipitation fields in a radial direction. The second effect is the loss of transmitted and received power, appearing as a decrease in system gain, and subsequently an underestimation of all power-based radar moments in the vicinity of the rods. The underestimation in radar reflectivity Z then leads to a negative bias of approximately 20 % in the actual rain rate if a Z – R relationship is applied. These detrimental effects on data quality led to the requirement of developing a new lightning protection concept. The new concept must minimise the effect on data quality but also provide sufficient protection from lightning strikes according to the existing regulations and requirements. Three possible lighting protection concepts are described in this paper: two using vertical rods of different diameters (16 and 40 mm) and one with horizontally placed rods outside the antenna aperture. Their possible influence on data quality is quantified through a dedicated measurement campaign by analysing resulting antenna patterns and precipitation sum products. Antenna patterns are analysed with respect to the side-lobe levels compared to antenna patterns without lightning protection and the original lightning protection. With the newly tested lightning rods, the apparent side-lobe levels are slightly increased compared to an antenna pattern taken without lightning protection but are within the accepted antenna specifications. Compared to the original lightning protection, a decrease of up to - 15 dB in apparent side-lobe levels is found for all tested lightning protection options. Beam blockage is substantially reduced compared to the existing lightning protection, as shown by the evaluation of quantitative precipitation estimation (QPE) sums. These results and some structural considerations are a solid basis to recommend the installation of four rods with a maximum 40 mm diameter for all 17 radar systems of the DWD weather radar network. [ABSTRACT FROM AUTHOR]

The paper reviews and evaluates a 30-year-long atmospheric CO2 data series measured at the Hegyhátsál tall-tower greenhouse gas monitoring site, a member of the World Meteorological Organization (WMO) Global Atmosphere Watch (GAW), US National Oceanic and Atmospheric Administration (NOAA), and pan-European Integrated Carbon Observation System (ICOS) networks. The paper also gives the technical description of the monitoring system and its changes over time and introduces the environment of the station. This low-elevation (248 m above mean sea level – m a.m.s.l.), mid-continental central European site shows a 3.90 ± 0.83 µmolmol-1 offset relative to the latitudinally representative marine boundary layer reference concentration, presumably due to European net anthropogenic emissions. The long-term trend (2.20 µmolmol-1yr-1) closely follows the global tendencies. In the concentration growth rate, the ENSO effect is clearly detectable with a 6–7-month lag time. The summer diurnal concentration amplitude is slightly decreasing due to the faster-than-average increase in the nighttime concentrations, which is related to the warming climate. The warming climate also caused a 0.96 ± 0.41 dyr-1 advance at the beginning of the summer CO2 -deficit season in the first half of the measurement period, which did not continue later. The summer CO2 -deficit season was extended by 9.0 ± 6.1 d during the measurement period. [ABSTRACT FROM AUTHOR]

While global streamflow reanalysis has been evaluated at different spatial scales to facilitate practical applications, its local performance in the time–frequency domain is yet to be investigated. This paper presents a novel decomposition approach to evaluating streamflow reanalysis by combining wavelet transform with machine learning. Specifically, the time series of streamflow reanalysis and observation are respectively decomposed and then the approximation components of reanalysis are evaluated against those of observed streamflow. Furthermore, the accumulated local effects are derived to showcase the influences of catchment attributes on the performance of streamflow reanalysis at different scales. For streamflow reanalysis generated by the Global Flood Awareness System, a case study is devised based on streamflow observations from the Catchment Attributes and Meteorology for Large-sample Studies. The results highlight that the reanalysis tends to be more effective in characterizing seasonal, annual and multi-annual features than daily, weekly and monthly features. The Kling–Gupta efficiency (KGE) values of original time series and approximation components are primarily influenced by precipitation seasonality. High values of KGE tend to be observed in catchments where there is more precipitation in winter, which can be due to low evaporation that results in reasonable simulations of soil moisture and baseflow processes. The longitude, mean precipitation and mean slope also influence the local performance of approximation components. On the other hand, attributes on geology, soils and vegetation appear to play a relatively small part in the performance of approximation components. Overall, this paper provides useful information for practical applications of global streamflow reanalysis. [ABSTRACT FROM AUTHOR]

Considered the Asian water tower, the Qinghai–Tibet Plateau (QTP) processes substantial permafrost, and its hydrological environments are spatially different and can be easily disturbed by changing permafrost and melting ground ice. Permafrost degradation compels melting permafrost to become an important source of surface runoff, changes the storage of groundwater, and greatly influences the hydrological processes in permafrost regions. However, the evidence linking permafrost degradation and hydrological processes on the QTP is lacking, which increases the uncertainties in the evaluation of the results of changing permafrost on the water resources. Stable isotopes offer valuable information on the connections between changing permafrost (ground ice) and water components. It is therefore particularly important to observe the changes in the stable isotopes of different waterbodies which can vary over hourly to annual timescales and truly capture the thawing signals and reflect the influence of permafrost (ground ice) on the regional hydrological processes. The Beiluhe Basin (BLH) in the hinterland of the QTP was selected; it integrates all the water components related to hydrological cycles well and is an ideal site to study the hydrological effect of permafrost change. This paper presents the temporal data of stable isotopes (δ18 O, δ D, and d -excess) in different waterbodies (precipitation, stream water, thermokarst lake, and groundwater) in the BLH produced between 2017 and 2022. Here, the first detailed stable isotope data of ground ice at 17 boreholes and 2 thaw slumps are presented. A detailed description of the sampling processes, sample pretreating processes, and isotopic data quality control is given. The data first described the full seasonal isotope amplitude in the precipitation, stream, and thermokarst lakes and delineated the depth isotopic variability in ground ice. In total, 554 precipitation samples, 2402 lake/pond samples, 675 stream water samples, 102 supra-permafrost water samples, and 19 sub-permafrost water samples were collected during 6 years of continuous sampling work. Importantly, 359 ground ice samples at different depths from 17 boreholes and 2 profiles were collected. This first dataset provides a new basis for understanding the hydrological effects of permafrost degradation on the QTP. It also provides support for the cryospheric study on the Northern Hemisphere. The dataset provided in this paper can be obtained at 10.5281/zenodo.10684110 (Yang, 2024). [ABSTRACT FROM AUTHOR]

Climate models, derived from process understanding, are essential tools in the study of climate change and its wide-ranging impacts. Hindcast and future simulations provide comprehensive spatiotemporal estimates of climatology that are frequently employed within the environmental sciences community, although the output can be afflicted with bias that impedes direct interpretation. Post-processing bias correction approaches utilise observational data to address this challenge, although they are typically criticised for not being physically justified and not considering uncertainty in the correction. This paper proposes a novel Bayesian bias correction framework that robustly propagates uncertainty and models underlying spatial covariance patterns. Shared latent Gaussian processes are assumed between the in situ observations and climate model output, with the aim of partially preserving the covariance structure from the climate model after bias correction, which is based on well-established physical laws. Results demonstrate added value in modelling shared generating processes under several simulated scenarios, with the most value added for the case of sparse in situ observations and smooth underlying bias. Additionally, the propagation of uncertainty to a simulated final bias-corrected time series is illustrated, which is of key importance to a range of stakeholders, such as climate scientists engaged in impact studies, decision-makers trying to understand the likelihood of particular scenarios and individuals involved in climate change adaption strategies where accurate risk assessment is required for optimal resource allocation. This paper focuses on one-dimensional simulated examples for clarity, although the code implementation is developed to also work on multi-dimensional input data, encouraging follow-on real-world application studies that will further validate performance and remaining limitations. The Bayesian framework supports uncertainty propagation under model adaptations required for specific applications, providing a flexible approach that increases the scope of data assimilation tasks more generally. [ABSTRACT FROM AUTHOR]

In the atmosphere, aerosols can originate from numerous sources, leading to the mixing of different particle types. This paper introduces an approach to the partitioning of aerosol mixtures in terms of backscattering coefficients. The method utilizes data collected from the Mie–Raman–fluorescence lidar, with the primary input information being the aerosol backscattering coefficient (β), particle depolarization ratio (δ), and fluorescence capacity (GF). The fluorescence capacity is defined as the ratio of the fluorescence backscattering coefficient to the particle backscattering coefficient at the laser wavelength. By solving a system of equations that model these three properties (β , δ and GF), it is possible to characterize a three-component aerosol mixture. Specifically, the paper assesses the contributions of smoke, urban, and dust aerosols to the overall backscattering coefficient at 532 nm. It is important to note that aerosol properties (δ and GF) may exhibit variations even within a specified aerosol type. To estimate the associated uncertainty, we employ the Monte Carlo technique, which assumes that GF and δ are random values uniformly distributed within predefined intervals. In each Monte Carlo run, a solution is obtained. Rather than relying on a singular solution, an average is computed across the whole set of solutions, and their dispersion serves as a metric for method uncertainty. This methodology was tested using observations conducted at the ATOLL (ATmospheric Observation at liLLe) observatory, Laboratoire d'Optique Atmosphérique, University of Lille, France. [ABSTRACT FROM AUTHOR]

Although research on the impacts of climate change on small- and medium-sized enterprises (SMEs) and their adaptation to climate change risks has recently received more attention, the focus on micro-businesses and household businesses is still very limited. Micro-businesses and household businesses are adversely affected by compound flooding events – a situation that will become more acute in the future – but there is little attention in the scientific literature to their adaptation options and actual implementation. Against this background, the paper analyzes the following research questions. How are micro-businesses already responding to flooding? Are micro-businesses willing to collectively invest in future proactive adaptation efforts in their neighborhoods? What are the key drivers of and barriers to adaptation? Based on scenario-based field experiments in Ho Chi Minh City, our results show that micro-businesses could play a much larger role in collective adaptation. Often overlooked in adaptation research, their willingness to engage in collective action under severe constraints is surprising. The conceptual framework presented in this paper helps us to understand the key drivers of and barriers to micro-business willingness to participate in collective adaptation activities. The most important key barriers for micro-businesses are limited financial capacity and lack of support from local authorities. However, micro-businesses are willing to contribute depending on the concrete adaptation measure and financing options. If no financial contribution is expected, almost 70 % are willing to participate in awareness-raising campaigns. And although their financial capacity is very limited, 39 % of micro-businesses would contribute financially if the costs were shared with other businesses in their neighborhood and with local authorities. In this context, micro-businesses should be much more involved in adaptation plans and measures. Through their local embeddedness, they can be important multipliers in strengthening adaptive capacity at the local level. [ABSTRACT FROM AUTHOR]

Scientific drilling in polar regions plays a crucial role in obtaining ice cores and using them to understand climate change and to study the dynamics of polar ice sheets and their impact on global environmental changes (sea level, ocean current cycle, atmospheric circulation, etc.). Mechanical rotary cutting is a widely used drilling method that drives the cutter to rotate to cut and drill through ice layers. It is necessary to conduct in-depth research on the brittle fracture behavior of ice and mechanical model and to analyze the factors and specific mechanisms (cutter's angle, rotation speed of the drill bit, and cutting depth) affecting cutting force for the rational design of ice core drill systems, improving the efficiency of ice core drilling and ensuring the drilling process runs smoothly. Therefore, in this paper, the process of ice cutting was observed, the fracture mechanics characteristics of the ice cutting process were analyzed, the formation process of ice chips was divided into three stages, and a mathematical model for the cutting force was established based on the observation results. The paper describes the damage conditions of ice failure and points out the factors and specific laws influencing cutting force. Furthermore, the cutting force generated under various experimental conditions was tested. Based on specified real-time variation curves of cutting force, the characteristics of cutting force were analyzed during the cutting and drilling process. Based on comparison to results of the average cutting force, the influence mechanism of various parameters acting on the cutting force was obtained. This proves the correctness of the mathematical model of the cutting force and provides a theoretical reference for the calculation of the cutting force during ice cutting and drilling in polar regions. [ABSTRACT FROM AUTHOR]

A 30-year (1980–2010) climatology of the major variables and terms of the transformed Eulerian-mean (TEM) momentum and thermodynamic equations is constructed by using four global atmospheric reanalyses: the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2); the Japanese 55-year Reanalysis (JRA-55); the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim); and the Climate Forecast System Reanalysis (CFSR). Both the reanalysis ensemble mean (REM) and the differences in each reanalysis from the REM are investigated in the latitude–pressure domain for December–January–February and for June–July–August. For the REM investigation, two residual vertical velocities (the original one and one evaluated from residual meridional velocity) and two mass streamfunctions (from meridional and vertical velocities) are compared. Longwave (LW) radiative heating and shortwave (SW) radiative heating are also shown and discussed. For the TEM equations, the residual terms are also calculated and investigated for their potential usefulness, as the residual term for the momentum equation should include the effects of parameterized processes such as gravity waves, while that for the thermodynamic equation should indicate the analysis increment. Inter-reanalysis differences are investigated for the mass streamfunction, LW and SW heating, the two major terms of the TEM momentum equation (the Coriolis term and the Eliassen–Palm flux divergence term), and the two major terms of the TEM thermodynamic equation (the vertical temperature advection term and the total diabatic heating term). The spread among reanalysis TEM momentum balance terms is around 10 % in Northern Hemisphere winter and up to 50 % in Southern Hemisphere winter. The largest uncertainties in the thermodynamic equation (about 50 %) are found in the vertical advection, for which the structure is inconsistent with the differences in heating. The results shown in this paper provide basic information on the degree of agreement among recent reanalyses in the stratosphere and upper troposphere in the TEM framework. [ABSTRACT FROM AUTHOR]